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interaction social data design patterns visualization charts
More...Uploaded via SlideShare as Apple Keynote
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vividliu
1 year ago
xiaoxiao sun
, PowerPoint Design Trainer
at My own sweet home
2 years ago
agrinyayev
, Interactive Designer
at BI-Digital Marketing
Tags data visualization social charts
2 years ago
David Hughes
, EMEA Delivery DIrector
at Experian
2 years ago
Caronne Carruthers-Taylor
, User Experience freelance consultant
at Holistic Focus
2 years ago
Readily available data (who doesn’t create data these days?)
Increasing standardization of formats (XBRL etc)
Flexible digital infrastructure (the pipes are connected)
Re-usable visualization platforms & elements (widgets, timelines, online spreadsheets etc)
Most importantly,
a growing acceptance (and, in turn, demand) for online data visualization
Online Data Visualization is “an idea whose time has come” due to a confluence of
Readily available data (who doesn’t create data these days?)
Increasing standardization of formats (XBRL etc)
Flexible digital infrastructure (the pipes are connected)
Re-usable visualization platforms & elements (widgets, timelines, online spreadsheets etc)
Most importantly,
a growing acceptance (and, in turn, demand) for online data visualization
Hugh MacLeod
http://gapingvoid.com/2007/12/31/social-objects-for-beginners/(via @mediajunkie)
Sensemaking
Jyri Engeström
http://www.zengestrom.com/blog/2007/08/what-makes-a-go.html
Jyri Engeström
http://www.zengestrom.com/blog/2007/08/what-makes-a-go.html
Jyri Engeström
http://www.zengestrom.com/blog/2007/08/what-makes-a-go.html
Jyri Engeström
http://www.zengestrom.com/blog/2007/08/what-makes-a-go.html
They also help us to frame a situation, to have foundational approaches to common messy problems
They also help us to frame a situation, to have foundational approaches to common messy problems
We used some design patterns to help describe how this circuit can be implemented...
Users need to learn the inbuilt strengths and limitations of different visualization techniques and how these might fit onto the data they are seeking to present.
Use when
People need to choose the most appropriate way to visualize a dataset.
Solution
Help the person determine their analysis or communication goals and then suggest a visualization approach that maps most closely onto their stated objectives and is appropriate for their dataset.
Many Eyes provides many different visualisation approaches and groups them by headings such as ‘analyse’ and ‘comparison’. Then next to each type of visualisation approach is a description of what that will highlight in the data set
Why
This chart suggestions flow chart breaks a wide range of visualisations into different communication outcomes, and variables of those outcomes
Rather than forcing people to concentrate on learning the merits of different visualization approaches (which can seem esoteric), guiding them through their communication and analysis goals helps people to focus on what they already know about their data and context they want to present it in.
How
Attempt to determine the communication or analysis goals the person has for their data visualization, including:
who they will be sharing the visualization with
what kind of data they will be visualizing
what outcomes they want the visualization to create
Based on these factors, suggest a visualization approach for the data, explaining why that approach is best suited to their goals.
Also present a range of other visualization approaches to the person, stressing their individual strengths and weaknesses.
Issues
This requires users to have a good understanding of the original data to be able to choose an appropriate visualization approach that communicates the dataset in the visual medium. An alternative approach by Many Eyes Wikified automatically chooses the visualization approach by performing a textual analysis on the dataset and choosing the best approach based on keywords (e.g. world uses a world map – heat map visualization), thus eliminating this problem.
Use when
Creating a visualization within a social space for the purposes of attaching an identity and communicating the meaning of the object in a visual way.
Solution
Let people integrate imagery and other media into their visualization to better communicate that visualization’s relevance and context.
Swivel queries Flickr with the chosen title of the visualization to provide images that can be used as a background for the visualization
Why
Decorating a visual representation provides it with an identity in much the same way that an avatar provides a user with an identity within a social network. This provides extra information about the visualization to other users, and contextualizes its place within a social space. In turn, this objectifies the visualization and allows it to exist on its own within the social environment.
It also reduces the cognitive load on other users, and allows the inherent meaning in the visualization to be communicated and consequently transferred to the community with greater ease.
How
Integrate with the search APIs of user generated content communities to access images and media that relate to the content of the visualization.
Issues
Assigning absolute meaning to media can be tricky, and often fails to communicate effectively across different cultures. People can ‘read’ images and media very differently.
Use when
One or more of the visualization parameters is variable (eg profit margin, unit cost)
One or more of the visualization parameters is ordered (eg time, scale, amount, location)
Solution
Instead of making the visualization a snapshot, make it an interface that lets a user playfully explore the data.
Gapminder enables a user to change or swap axes to look for correlations, as well as tweak other aspects of complex datasets.
Create ways for users to change how a dataset is represented in a visualization allowing the impact of any changes they make to be immediately reflected.
With ordered data, allow users to sort the data. eg: by labels, values and data order.
Give users the ability to reconfigure a visualization schema. eg: swap the X and Y axis on a two dimensional graph.
Pay attention to usability when designing visualization interfaces, eg: clearly communicate which parameter is selected, and what visualization elements it affects.
Why
Being able to tweak a parameter value and see how it affects a visualization helps communicate the relationship that parameter has to the whole visual analysis. This can help people see trends and make sense of complex datasets more quickly than with static visualizations.
How
Build controls into the interface that enable users to perform actions such as resorting the data, excluding certain parts of the data, or changing a variable that reflects the outcome of the data. This can be done through the use of drop down menus, radio buttons, check boxes and sliders.
Use when
Wanting to promote discussion of visualization details and sub-elements.
Solution
Give people the ability to make annotations that are consistent and are not disruptive in any way to the underlying visualisation.
Wikinvest allows users to annotate a company’s share price performance with non-disruptive annotations.
Why
Being able to create non-disruptive annotations adds knowledge to the visualization, the use of non-disruptive annotations means that all members of the community are talking in the same visual language which makes community sensemaking an easier process.
How
Instead of giving people a set of drawing, arrow and box tools as can be found in some desktop software, provide them with a single method of annotating a visualization that is in keeping with the visualization approach used (eg. highlight bars in a bar chart, show the height of ranges in a flow graph).
Use when
Interactive visualization is used to support discussion of a dataset.
Solution
Allow people to store and retrieve configurations of a data visualization.
Many Eyes allows a snapshot of the current visualization state to be saved, and attached to a separate text based comment.
Why
Being able to see what another person saw is an important way of understanding what they are trying to communicate.
Collecting snapshots along with discussion is a good way to illustrate the evolution of understanding around a dataset.
How
When commenting on a data visualization, attach a ‘snapshot’ of what the visualization currently looks like to the comment.
When selecting a comment, configure the visualization to reflect the ‘snapshot’ associated with that comment.
Issues
Snapshots do not provide a good overview of the insight that a community has extracted from a visualisation. It is necessary to look through each snapshot and comment to get a sense of what has transpired.
Use when
Interactive visualization is used to support discussion of a dataset.
Solution
Allow people to store and retrieve configurations of a data visualization.
Many Eyes allows a snapshot of the current visualization state to be saved, and attached to a separate text based comment.
Why
Being able to see what another person saw is an important way of understanding what they are trying to communicate.
Collecting snapshots along with discussion is a good way to illustrate the evolution of understanding around a dataset.
How
When commenting on a data visualization, attach a ‘snapshot’ of what the visualization currently looks like to the comment.
When selecting a comment, configure the visualization to reflect the ‘snapshot’ associated with that comment.
Issues
Snapshots do not provide a good overview of the insight that a community has extracted from a visualisation. It is necessary to look through each snapshot and comment to get a sense of what has transpired.
Hugh Macdonald @insanitycured
Reuben Stanton @absent
Nifeli Stewart
Pete Williams @rexster & Bevan MacLeod at Deloitte Digital
and the support of
ACID, the Australasian CRC for Interaction Design http://acid.net.au
RMIT University http://rmit.edu.au